[scikit-learn] Fwd: libmf bindings

Gael Varoquaux gael.varoquaux at normalesup.org
Wed Nov 2 12:32:15 EDT 2016

Given that we'd love to get rid of our libsvm/liblinear biddings, I would
be more in favor of improving our matrix factorization code rather than
including this code.

That said, +1 for missing data imputation with matrix factorization, once
we're done with the current PRs on missing data.


On Wed, Nov 02, 2016 at 12:10:40PM -0400, Andy wrote:

> -------- Forwarded Message --------
> Subject: libmf bindings
>    Date: Wed, 2 Nov 2016 11:38:00 -0400
>    From: sam royston <sfoxroyston at gmail.com>
>      To: scikit-learn-owner at python.org

> Hi,

> Thanks for all your hard work on this useful tool! I'm hoping to contribute
> bindings to Chih-Jen Lin's libmf: https://www.csie.ntu.edu.tw/~cjlin/libmf/. It
> looks like you guys have functionality for NMF, but used only in the
> decomposition/ dimensionality reduction setting (and obviously only with
> non-negative values). Id like to add functionality in the form python wrappers
> for libmf, much like you have for Chih-Jen Lin's other libraries libsvm and
> liblinear.

> Libmf is very efficient and offers great functionality for missing data
> imputation, recommendation systems and more.

> I have already written bindings using ctypes, but I see that you have you
> Cython for libsvm and liblinear - is it necessary that I switch to that
> interface?

> Let me know what you think of a contribution like this.

> Thanks,
> Sam

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    Gael Varoquaux
    Researcher, INRIA Parietal
    NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France
    Phone:  ++ 33-1-69-08-79-68
    http://gael-varoquaux.info            http://twitter.com/GaelVaroquaux

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